Today users of user equipments (UEs) like cellular phones, PDA's (personal digital assistants), wireless broadband connected computers and user of other electronic equipment capable of wireless mobile communication have limited possibility of efficiently predicting face-to-face encounters with friends at a present or future location, based on their friends' patterns of actual movements and locations.
By using existing systems a user of a UE can share presence (physical location) information and to certain degree information about future presence, based on calendar events or direct manual input from the user. However, existing systems are often not optimized for performing automated estimates of the likeliness of near future presence of friends at the user's current or future location based on a shared record of actual presence and movements over time and space.
An example of a known technique that relates to predicting a future location of a mobile node is described in US 2009/054043 A1. In this document a computer-implemented method includes determining a current location of a first mobile node, determining a location of at least a second mobile node wherein the second mobile node is associated with the first mobile node via a social network, and generating a list including at least one candidate destination determined, at least in part, according to the location of the first mobile node and the location of the second mobile node. For each candidate destination on the list, a probability that the first mobile node is in route to that candidate destination location can be calculated. A candidate destination can be selected, according to the probabilities, from the list as a predicted future location of the first mobile node. The predicted future location of the first mobile node can be output.
Though the known method described above may predict a future location of a mobile node, it is limited to use of movements for individual mobile nodes when predicting a future location, which provides a limitation when predicting face-to-face encounters with a number of friends using a respective mobile user equipment.
Accordingly, the applicant has appreciated that there is a need of improvement in terms predicting of a presence of a mobile user equipment.